model = ModelWithDefault(foo="foo", bar="bar")
    assert jsonable_encoder(model) == {"foo": "foo", "bar": "bar", "bla": "bla"}
    assert jsonable_encoder(model, exclude_unset=True) == {"foo": "foo", "bar": "bar"}
    assert jsonable_encoder(model, exclude_defaults=True) == {"foo": "foo"}
    assert jsonable_encoder(model, exclude_unset=True, exclude_defaults=True) == {
        "foo": "foo"
    }

        m.region(pos, input.length());
        return m.lookingAt();
    }

    public String region() {
        return input.substring(markPos, pos);
    }

    /**
     * Moves the position to the next instance of the given character, or the end of the input if not found.
     */
    public void find(char c) {
        int cpos = pos;
        while (cpos < input.length()) {

    }

    /**
     * Converts this compat model InputSource to an API model InputSource.
     * This method is used for converting between the compat model and the API model.
     *
     * @return the equivalent API model InputSource
     */
    public org.apache.maven.api.model.InputSource toApiSource() {
        return org.apache.maven.api.model.InputSource.of(modelId, location);
    }

            "spanNulls": false,
            "stacking": {
              "group": "A",
              "mode": "none"
            },
            "thresholdsStyle": {
              "mode": "off"
            }
          },
          "mappings": [],
          "thresholds": {
            "mode": "absolute",
            "steps": [
              {
                "color": "green",

import jetbrains.buildServer.configs.kotlin.Project
import model.CIBuildModel
import model.FunctionalTestBucketProvider
import model.Stage
import model.TestCoverage

const val DEFAULT_FUNCTIONAL_TEST_BUCKET_SIZE = 50
const val DEFAULT_LINUX_FUNCTIONAL_TEST_BUCKET_SIZE = 20
const val DEFAULT_MACOS_FUNCTIONAL_TEST_BUCKET_SIZE = 20

class FunctionalTestProject(
    val model: CIBuildModel,

		}
	}

	r = dryDB.Table("(?) as u", DB.Model(&User{}).Select("name")).Find(&User{}).Statement
	if !regexp.MustCompile("SELECT \\* FROM \\(SELECT .name. FROM .users. WHERE .users.\\..deleted_at. IS NULL\\) as u WHERE .u.\\..deleted_at. IS NULL").MatchString(r.Statement.SQL.String()) {
		t.Errorf("Table with escape character, got %v", r.Statement.SQL.String())
	}

import jetbrains.buildServer.configs.kotlin.BuildSteps
import jetbrains.buildServer.configs.kotlin.ParameterDisplay
import model.CIBuildModel
import model.PerformanceTestBuildSpec
import model.PerformanceTestType
import model.Stage

class PerformanceTest(
    model: CIBuildModel,
    stage: Stage,
    performanceTestBuildSpec: PerformanceTestBuildSpec,
    description: String,
    performanceSubProject: String,

import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;

import org.apache.maven.api.model.Model;
import org.apache.maven.model.v4.MavenStaxReader;

/**
 * A utility class that analyzes Maven POM files to identify memory usage patterns and potential memory optimizations.

The same way, this database wouldn't receive a Pydantic model (an object with attributes), only a `dict`.

You can use `jsonable_encoder` for that.

It receives an object, like a Pydantic model, and returns a JSON compatible version:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.

import org.apache.maven.model.PluginContainer;
import org.apache.maven.model.ReportPlugin;
import org.apache.maven.model.Reporting;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;
import org.apache.maven.model.merge.MavenModelMerger;
import org.codehaus.plexus.util.StringUtils;

/**
 * Handles inheritance of model values.
 *